首页|艾比湖流域植被NPP时空演变特征及其驱动因素

艾比湖流域植被NPP时空演变特征及其驱动因素

扫码查看
植被净初级生产力(NPP)是监测植被生长状况的重要参数,也是评价生态系统健康状况的重要指标.艾比湖流域是新亚欧大陆桥的一道重要生态安全屏障,研究植被NPP时空变化特征及其驱动因素,对保障流域生态环境健康稳定具有重要意义.基于气象数据、NDVI数据、植被类型数据,采用CASA模型估算艾比湖流域2001-2020年的植被NPP,采用热点分析、变异系数、趋势分析等方法,揭示植被NPP时空分布格局及演变特征;采用偏相关分析结合参数最优地理探测器模型揭示植被NPP的影响因素.结果表明:(1)2001-2020年艾比湖流域植被NPP多年平均值为199.67 gC m-2 a-1,整体呈波动上升趋势,增长率为1.83 gC m-2 a-1.(2)空间分布集聚特征明显,整体呈四周高中间低的分布格局,61.79%的区域植被NPP呈增加趋势,河流沿岸的绿洲植被NPP显著增加.(3)植被NPP与气象因子呈正相关关系,与降水相关性最强;NPP值随高程和坡度增加呈先增后减的趋势,随坡向变化差异不明显;不同植被类型和不同土壤类型的NPP值差异明显,土地利用变化对植被NPP具有双重影响.(4)土地利用类型和植被类型是影响植被NPP空间分异的主要因子,因子交互作用表现为双因子增强或非线性增强,基于风险探测确定出适宜植被生长的范围或类型.研究结果可为决策者制定艾比湖流域可持续发展方案提供理论依据.
Spatiotemporal dynamics and driving factors of net primary productivity in the Ebinur Lake Basin
Net primary productivity(NPP)is a key parameter for monitoring vegetation growth and an important indicator for evaluating ecosystem health.The Ebinur Lake Basin is an important ecological security barrier of the new Eurasian Land Bridge.Therefore,studying the temporal and spatial variation characteristics and driving factors of NPP in the Ebinur Lake Basin is crucial for ensuring the health and stability of its ecological environment.In this study,the CASA(Carnegie-Ames-Stanford Approach)model was used to estimate the NPP of the Ebinur Lake Basin from 2001 to 2020 based on meteorological data,Normalized Difference Vegetation Index(NDVI)data and vegetation type data.Hotspot analysis,coefficient of variation,and trend analysis were used to reveal the temporal and spatial distribution patterns,as well as the evolutionary characteristics of NPP.Additionally,partial correlation analysis was combined with the optimal parameters-based geographical detector(OPGD)model to identify the influencing factors of NPP.The results showed that:(1)The NPP in the Ebinur Lake Basin fluctuated and increased from 2001 to 2020,with a multi-year average NPP value of 199.67 gC m-2 a-1 and a growth rate of 1.83 gC m-2 a-1.(2)The spatial distribution of NPP had obvious spatial agglomeration characteristics,and the spatial differentiation of NPP showed a pattern of being surrounded by high and low in the middle.The NPP increased in 61.79%of regions,with significant increases concentrated in oases along rivers.(3)The NPP was positively correlated with meteorological factors,and had the strongest correlation with precipitation.NPP increased and then decreased with the increase of elevation and slope,and no significant difference was observed in NPP with the variation in aspect.There were obvious differences in the NPP values of different vegetation types and soil types.The change of land use had both positive and negative effects on NPP.(4)Land use type and vegetation type were the main factors affecting the spatial and temporal differentiation of NPP in the Ebinur Lake Basin.The effects of different factors showed bivariate enhancement or nonlinear enhancement,and the most suitable range or type of vegetation growth among the factors were determined based on the risk detector.The results of this study can be used to monitor the vegetation growth and ecosystem health in the basin,and provide a theoretical foundation for decision makers to formulate a sustainable development program for the Ebinur Lake Basin.

net primary productivityCASA modeloptimal parameters-based geographical detectordriving factorsEbinur Lake Basin

罗健梅、阿布都热合曼·哈力克、段越帆、姚凯旋、姚磊、唐华、布威阿依谢姆·吐合提

展开 >

新疆大学地理与遥感科学学院,乌鲁木齐 830017

新疆大学绿洲生态重点实验室,乌鲁木齐 830017

新疆大学智慧城市与环境建模自治区普通高校重点实验室,乌鲁木齐 830017

净初级生产力 CASA模型 参数最优地理探测器 驱动因素 艾比湖流域

2025

生态学报
中国生态学学会,中国科学院生态环境研究中心

生态学报

北大核心
影响因子:2.191
ISSN:1000-0933
年,卷(期):2025.45(1)